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Nicola Borri Publications

Publish Date
Working Paper
Abstract

We show that the higher-orders and their interactions of the common sparse linear factors can effectively subsume the factor zoo. To this extend, we propose a forward selection Fama-MacBeth procedure as a method to estimate a high-dimensional stochastic discount factor model, isolating the most relevant higher-order factors. Applying this approach to terms derived from six widely used factors (the Fama-French five-factor model and the momentum factor), we show that the resulting higher-order model with only a small number of selected higher-order terms significantly outperforms traditional benchmarks both in-sample and out-of-sample. Moreover, it effectively subsumes a majority of the factors from the extensive factor zoo, suggesting that the pricing power of most zoo factors is attributable to their exposure to higher-order terms of common linear factors.

Working Paper
Abstract

The European Union Emission Trading System is a prominent market-based mechanism to reduce emissions. While the theory is well-understood, we are the first to study the whole cap-and-trade mechanism as a financial market. Analyzing the universe of transactions in 2005-2020 (more than one million records of granular transaction data), we show that this market features significant inefficiencies undermining its goals. First, about 40% of firms never trade in a given year. Second, many firms only trade during surrendering months, when compliance is immediate and prices are predictably high. Third, a number of operators engage in speculative trading, exploiting private information.

Working Paper
Abstract

We propose a new non-linear single-factor asset pricing model π‘Ÿπ‘–π‘‘ = β„Ž( 𝑓𝑑 πœ†π‘–) + πœ–π‘–π‘‘ . Despite its parsimony, this model represents exactly any non-linear model with an arbitrary number of factors and loadings – a consequence of the Kolmogorov-Arnold representation theorem. It features only one pricing component β„Ž( 𝑓𝑑 πœ†π‘–), comprising a nonparametric link function of the time-dependent factor and factor loading that we jointly estimate with sieve-based estimators. Using 171 assets across major classes, our model delivers superior cross-sectional performance with a low-dimensional approximation of the link function. Most known finance and macro factors become insignificant controlling for our single-factor.